Perfect Secrecy in IoT A Hybrid Combinatorial-Boolean Approach

Perfectly-secure cryptography is a branch of information-theoretic cryptography. A perfectly-secure cryptosystem guarantees that the malicious third party cannot guess anything regarding the plain text or the key, even in the case of full access to the cipher text. Despite this advantage, there are only a few real-world implementations of perfect secrecy due to some well-known limitations. Any simple, straightforward modeling can pave the way for further advancements in the implementation, especially in environments with time and resource constraints such as IoT. This book takes one step towards this goal via presenting a hybrid combinatorial-Boolean model for perfectly-secure cryptography in IoT.

In this book, we first present an introduction to information-theoretic cryptography as well as perfect secrecy and its real-world implementations. Then we take a systematic approach to highlight information-theoretic cryptography as a convergence point for existing trends in research on cryptography in IoT. Then we investigate combinatorial and Boolean cryptography and show how they are seen almost everywhere in the ecosystem and the life cycle of information-theoretic IoT cryptography. We finally model perfect secrecy in IoT using Boolean functions, and map the Boolean functions to simple, well-studied combinatorial designs like Latin squares.

This book is organized in two parts. The first part studie s information-theoretic cryptography and the promise it holds for cryptography in IoT. The second part separately discusses combinatorial and Boolean cryptography, and then presents the hybrid combinatorial-Boolean model for perfect secrecy in IoT.

Introduction.- A Review on Perfect Secrecy.- Perfect Secrecy and Boolean Functions with Applications in Resource-Constrained IoT Environments.- Cryptography in IoT.- Resilient functions.- Modeling a General Cryptographic Algorithm.- Latin Squares and Cryptography.- Perfectly-Secure Encryption Modeled Using Latin Squares.- Conclusion.

Behrouz Zolfaghari has received his Ph.D in Computer Engineering from Amirkabir University, Tehran, Iran. He has done a postdoc at IIT (Indian Institute of Technology) Guwahati, India.He is currently doing another postdoc in the University of Guelph, Canada. His research areas includes VLSI Design, High-Performance Computing, Information-Theoretic Cryptography,Hardware-Oriented Cryptography,  AI-assisted Cryptographyand Secure AI.

Khodakhast Bibak is an Assistant Professor at the Department of Computer Science and Software Engineering at Miami University. Previously, he was a Postdoctoral Research Associate (September 2017 - August 2018) in the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. Before this, Khodakhast was a Postdoctoral Research Fellow (May-August 2017) at the Department of Computer Science, University of Victoria, from where he also received his PhD (April 2017). He earned a Master of Mathematics degree (April 2013) at the Department of Combinatorics and Optimization, University of Waterloo, where he was also a member of the Centre for Applied Cryptographic Research (CACR). Khodakhast’s research interests are Cybersecurity, Applied Cryptography, Quantum Information Science (QIS), Artificial Intelligence, and the related areas.